Predicting Programmers' Ability to Modify Software.

Abstract

This report describes the second experiment in a program of research designed to identify characteristics of computer software which are related to its psychological complexity. Thirty-six experienced programmers were given unlimited time to make specified modifications to a preliminary program and three experimental programs. The correctness of the modification and the time required to make each modification served as dependent variables. Results indicated that the difficulty of the modification was significantly related to the time to solution. This relationship was described by a hyperbolic function relating time to the number of statements to be inserted in the code. Modest effects on the score and time were observed for order presentation, suggesting a learning effect. On two of the three programs studied, better modifications were made when the control flow of the original programs was well-structured. No performance effects were related to the absence of comments or the type of comments (in-line versus global) used. Moderate relationships with the criteria were observed for several complexity metrics, and these were strongest where metrics were obtained from the modified code rather than the original programs.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1978
Accession Number
ADA056079

Entities

People

  • B. Curtis
  • L. T. Love
  • M. A. Borst
  • S. B. Sheppard

Organizations

  • General Electric

Tags

Communities of Interest

  • Biomedical
  • Human Systems
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Applied Psychology
  • Cognition
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Computers
  • Debugging
  • Department Of Defense
  • Human Factors Engineering
  • Information Processing
  • Information Science
  • Information Systems
  • Military Research
  • Psychology
  • Regression Analysis
  • Software Development

Fields of Study

  • Psychology

Readers

  • Computational Linguistics
  • Regression Analysis.
  • Software Engineering